100% accuracy in automatic face recognition
100% accuracy in automatic face recognition
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DOI：
10.1126/science.1149656
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发表时间：
2008-01-25
期刊：
影响因子：
56.9
通讯作者：
Burton, A. M.
中科院分区：
文献类型：
--
作者：
Jenkins, R.;Burton, A. M.
准确的人脸识别对于许多安全应用至关重要。当前的自动人脸识别系统被光照和姿势的自然变化击败，这通常比身份的变化更深刻地影响人脸图像。唯一能够可靠地科普这种变化的系统是熟悉相关面孔的人类观察者。我们通过使用图像平均来模拟人类的熟悉度，从而从自然变化的照片中获得稳定的人脸表示。这个简单的过程将行业标准人脸识别算法的准确率从54%提高到了100%，将熟悉的人类的强大性能带到了自动化系统中。
Accurate face recognition is critical for many security applications. Current automatic face-recognition systems are defeated by natural changes in lighting and pose, which often affect face images more profoundly than changes in identity. The only system that can reliably cope with such variability is a human observer who is familiar with the faces concerned. We modeled human familiarity by using image averaging to derive stable face representations from naturally varying photographs. This simple procedure increased the accuracy of an industry standard face-recognition algorithm from 54% to 100%, bringing the robust performance of a familiar human to an automated system.